
High-throughput sequencing continues to produce an immense volume of information that is processed and assembled into mature sequence data. Data analysis tools are urgently needed that leverage the embedded DNA sequence polymorphisms and consequent changes to restriction sites or sequence motifs in a high-throughput manner to enable biological experimentation. CisSERS was developed as a standalone open source tool to analyze sequence datasets and provide biologists with individual or comparative genome organization information in terms of presence and frequency of patterns or motifs such as restriction enzymes. Predicted agarose gel visualization of the custom analyses results was also integrated to enhance the usefulness of the software. CisSERS offers several novel functionalities, such as handling of large and multiple datasets in parallel, multiple restriction enzyme site detection and custom motif detection features, which are seamlessly integrated with real time agarose gel visualization. Using a simple fasta-formatted file as input, CisSERS utilizes the REBASE enzyme database. Results from CisSERS enable the user to make decisions for designing genotyping by sequencing experiments, reduced representation sequencing, 3'UTR sequencing, and cleaved amplified polymorphic sequence (CAPS) molecular markers for large sample sets. CisSERS is a java based graphical user interface built around a perl backbone. Several of the applications of CisSERS including CAPS molecular marker development were successfully validated using wet-lab experimentation. Here, we present the tool CisSERS and results from in-silico and corresponding wet-lab analyses demonstrating that CisSERS is a technology platform solution that facilitates efficient data utilization in genomics and genetics studies.
570, Genomics - methods, Genotype, Genetic - genetics, Science, User-Computer Interface, Humans, Computer Simulation, Polymorphism, Nucleotide Motifs, 3' Untranslated Regions, DNA - methods, Genome, Polymorphism, Genetic, Q, R, Nucleotide Motifs - genetics, Computational Biology, Genomics, Sequence Analysis, DNA, 3' Untranslated Regions - genetics, Genome - genetics, 004, Computational Biology - methods, Medicine, Sequence Analysis, Software, Research Article
570, Genomics - methods, Genotype, Genetic - genetics, Science, User-Computer Interface, Humans, Computer Simulation, Polymorphism, Nucleotide Motifs, 3' Untranslated Regions, DNA - methods, Genome, Polymorphism, Genetic, Q, R, Nucleotide Motifs - genetics, Computational Biology, Genomics, Sequence Analysis, DNA, 3' Untranslated Regions - genetics, Genome - genetics, 004, Computational Biology - methods, Medicine, Sequence Analysis, Software, Research Article
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